AI Prompt Engineering: Generative AI & Context Engineering

About this course

Learn AI prompt engineering and context engineering to use generative AI more effectively for writing, research, coding assistance, document analysis and everyday work.

This practical course takes you from prompt fundamentals to multimodal AI tasks involving text, documents, images and data. You will learn how to give AI clearer instructions, supply relevant context, request useful output formats and evaluate the results.

Through explanations, demonstrations and practical projects, you will develop a repeatable approach to working with AI—one that includes checking its answers and understanding its limitations.

What you will learn

Generative AI fundamentals: Understand large language models, tokens, context windows, hallucinations and how model capabilities affect your results.

AI prompt engineering techniques: Practise zero-shot and few-shot prompting, role-based instructions, prompt refinement and prompt chaining. Learn when examples and clear constraints can improve an answer.

Context engineering: Organize goals, background information, source material, examples and requirements so the model has the information it needs to complete a task.

Structured outputs: Request tables, lists, JSON and CSV-style responses that are easier to review and reuse.

Multimodal AI: Work with documents, PDFs, images, screenshots and spreadsheets using tools that support those inputs. Practise summarizing information, extracting details, interpreting content and checking the results against the source.

Practical AI workflows: Break larger tasks into stages such as research, analysis, drafting, verification and final output. Create reusable prompt templates for recurring work.

Output evaluation: Assess accuracy, relevance, clarity and consistency. Recognize unsupported claims, verify important information and decide when human review is n

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